EE Systems Seminar

BIO: Iñaki Esnaola is a Lecturer (Assistant Professor) in the Department of Automatic Control and Systems Engineering at the University of Sheffield, UK, and a Visiting Research Collaborator in the Department of Electrical Engineering at Princeton University, NJ. He received his MSc in Electrical Engineering from the University of Navarra, Spain in 2006 and a PhD in Electrical Engineering from the University of Delaware, Newark, DE in 2011. He is currently a Lecturer in the Department of Automatic Control and Systems Engineering at The University of Sheffield, and a Visiting Research Collaborator in the Department of Electrical Engineering at Princeton University, NJ. In 2010-2011 he was a Research Intern at Bell Laboratories, Alcatel-Lucent, Holmdel, NJ, and in 2011-2013 he was a Postdoctoral Research Associate at Princeton University. His research interests include information theory and communication theory with an emphasis on the application to electricity grid problems.

Abstract:
The smart grid paradigm is founded on the integration of existing power grids with advanced sensing and communication infrastructure. While the benefits provided by this setting are crucial for the future development of power grids, it also increases the dependency on system monitoring procedures and opens the door to security threats. In this talk, we first address the privacy problem posed by the installation of smart meters at the consumer level. Information theoretic tools provide quantifiable privacy guarantees for power consumption profiles modelled as memoryless random processes but have not yet been successfully used in realistic settings with complex consumption profiles. We propose privacy guarantees for a wide range of random processes based on non-probabilistic permuting channel models for the system. In the second part of the talk we shift our attention to the state estimation problem at the transmission level. One of the main contingencies faced by state estimation procedures is intentionally corrupted data by a malicious attacker. We overview recent results and introduce new information-theoretic attacks that minimize the amount of information obtained by the operator from the grid and the probability of attack detection.